Procuring cooperative intelligence in autonomous vehicles for object detection through data fusion approach

Daniel, Alfred; Subburathinam, Karthik; Muthu, BalaAnand; Rajkumar, N.; Kadry, Seifedine; Mahendran, Rakesh Kumar; Pandian, Sanjeevi

doi:10.1049/iet-its.2019.0784

Cited by 49 publications

(11 citation statements)

References 23 publications

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“…It is especially suitable for the study of the stability law of the slope in a large area. It mainly includes the natural history analysis method, graphic analysis method, engineering geology analogy method, and expert system [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Stability Evaluation of Rock Slope in Hydraulic Engineering Based on Improved Support Vector Machine Algorithm

Zhang

2021

Complexity

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The safety problem of the slope has always been an important subject in engineering geology, which has a wide range of application background and practical significance in reality. How to correctly evaluate the stability of the slope and obtain the parameters of the slope has always been the focus of research and production personnel at home and abroad. In recent years, various artificial intelligence calculation methods have been applied to the field of rock engineering and engineering geology, providing some new ideas for the solution of slope stability analysis and parameter back analysis. Support vector machine (SVM) algorithm has unique advantages and generalization in dealing with finite samples and highly complex and nonlinear problems. At present, it has become a research hotspot of intelligent methods and has been widely paid attention to in various application fields of slope engineering. In this paper, a cuckoo search algorithm-improved support vector machine (CS-SVM) method is applied to slope stability analysis and parameter inversion. Aiming at the problem of selecting kernel function parameters and penalty number of SVM, a method of using cuckoo search algorithm to improve support vector machine was proposed, and the global optimization ability of cuckoo search algorithm was used to improve the algorithm. Aiming at the slope samples collected, the classification algorithm of support vector machine (SVM) was used to identify the stable state of the test samples, and the improved SVM algorithm was used to analyze the safety factor of the test samples. The results show that the proposed method is reasonable and reliable. Based on the inversion of the permeability coefficient of the test samples by the improved support vector machine, the comparison between the inversion value and the theoretical value shows that it is basically feasible to invert the permeability coefficient of the dam slope by the improved support vector machine.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Stability Evaluation of Rock Slope in Hydraulic Engineering Based on Improved Support Vector Machine Algorithm

Zhang

2021

Complexity

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“…As inferred from the equation (16) where 𝑓 𝑙 𝑗𝑖 denotes the traffic flow from j to i on road segment l, 𝑃 𝑗𝑖 denotes the total flow from j to i.…”

Section: Iot Driven Intelligent Transportation Framework (Iotditf)mentioning

confidence: 99%

“…Sustainability planning involves understanding what preventive treatment refers to safety. Sustainable development aims at an optimal balance between economic, social and environmental goals [16,17]. Figure 1 shows the internet of Things in the intelligent transportation system.…”

Section: Significance About the Researchmentioning

confidence: 99%

Environmental and Economic Benefits of Establishing a Sustainable Transportation System Based on Internet of Things

Qi¹

2021

Preprint

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The Internet of Things (IoT) is a modern concept which has turned the conventional way of living into a high technology lifestyle. The transformations caused by IoT are the smart city, smart homes, pollution control, energy savings, smart transport and the smart industries. Transportation infrastructure has a huge impact on sustainable development. Sustainable development concerns over environmental quality, social, economic vitality, and climate variation strategic planning due to increasing CO2 have come together to generate an increasing interest in an alternative approach. Sustainable development is very important in any pattern, particularly in the century, and it is therefore very necessary to address sustainable development. In the transport sector, sustainable development can be divided into three main areas: society, economy and environment. Consequently, in this paper, the IoT driven Intelligent Transportation Framework (IoTDITF) has been proposed to establish a sustainable transportation system. Sustainable transport approaches include demand management, price policies, improvement of vehicle technology, clean fuels and integrated land use and transport scheduling. This paper attempts to analyze certain economic problems, such as realistic pricing and the development of an integrated transport network.The findings serve as a guide for policymakers, transport modelers, and planners to adopt indicators on an operating level, thereby simplifying the aggressive task of selecting an indicator.

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“…Filter‐based methods, such as EKF [5] and UKF [6], combine inertia and visual information. [7] and [8] applied optimization‐based strategies to fusion tasks of LiDAR and camera, which maintain measurements in a buffer and optimize them simultaneously to improve accuracy. However, most sensor fusion methods mainly focused on information obtained from eyes and ignore rich information from other sources.…”

Section: Introductionmentioning

confidence: 99%

Adding ears to intelligent connected vehicles by combining microphone arrays and high definition map

Jiang

Yang

Wijaya

et al. 2021

IET Intelligent Trans Sys

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Ears are responsible for the sense of hearing, which is indispensable for a human to understand the environment. It is similar to an intelligent vehicle where acoustical data contains useful and valuable information to comprehend the environment to enable autonomous driving. One important application of acoustical data processing is to localize sound sources. However, due to the complexity of microphone array setup and the unstable localization performance against noises, few research articles tried to localize surrounding vehicles based on on-board microphone arrays. The main contribution is the first implementation to combine roof-mounted microphones and high definition maps as vehicle' s ears for online 3D localization of surround vehicles. This article designed a six-microphones sensor array dedicated to the on-board application and improved sound source localization algorithms using the observer technique to adapt to dynamic driving scenarios. A map-based localization enhancement method is also proposed to make the system more robust to noises and model errors. Feasibility tests are conducted with real vehicles in the scenarios of pass-by and overtaking. Experimental results validate the feasibility of using microphones to localize surrounding vehicles with lane-level accuracy. INTRODUCTIONAcoustical data contains useful and valuable information for the comprehension of the environment to enable autonomous driving. However, in the current research of intelligent connected vehicles (ICV), acoustical data processing is not valued as much as other perception techniques. The most widely employed sensors in ICV are microwave radar [1], LiDAR [2], and cameras [3]. These sensors can provide precise and detailed information of the traffic scene for localization and detection. For this reason, these sensors are also called the eyes of ICV. Nevertheless, in some situations, the eyes could be temporarily blind and cause road safety disasters. For example, LiDAR is sensitive to rainy days, while cameras can be influenced by fog, smoke, and dirt on the lens. To address these problems, plenty of sensor fusion methods were proposed to compensate for the limitations of using a single sensor. [4]. Filter-based methods, such as EKF [5] and UKF [6], combine inertia and visual information. [7] and [8] This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Procuring cooperative intelligence in autonomous vehicles for object detection through data fusion approach

Cited by 49 publications

References 23 publications

[Retracted] Stability Evaluation of Rock Slope in Hydraulic Engineering Based on Improved Support Vector Machine Algorithm

[Retracted] Stability Evaluation of Rock Slope in Hydraulic Engineering Based on Improved Support Vector Machine Algorithm

Environmental and Economic Benefits of Establishing a Sustainable Transportation System Based on Internet of Things

Adding ears to intelligent connected vehicles by combining microphone arrays and high definition map

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